In this video we go through the most basic and essential tensor operations that really build the foundation to TensorFlow 2.0 and is important to know before moving on to building neural networks which we will start with in the next tutorial! :)

Knowledge in Linear Algebra is very important to have an easier time understanding many tensor operations we go through so I would view as a prerequisite. I think if you don't have that then this series by 3Blue1Brown can be helpful:
https://www.youtube.com/playli....st?list=PLZHQObOWTQD

I learned a lot and was inspired to make these TensorFlow videos by the TensorFlow Specialization on Coursera. Below you'll find both affiliate and non-affiliate links, the pricing for you is the same but a small commission goes back to the channel if you buy it through the affiliate link.
affiliate: https://bit.ly/3t3tgI5
non-affiliate: https://bit.ly/3kZgN5B

GitHub Repository:
https://github.com/aladdinpers....son/Machine-Learning

✅ Equipment I use and recommend:
https://www.amazon.com/shop/aladdinpersson

❤️ Become a Channel Member:
https://www.youtube.com/channe....l/UCkzW5JSFwvKRjXABI

✅ One-Time Donations:
Paypal: https://bit.ly/3buoRYH
Ethereum: 0xc84008f43d2E0bC01d925CC35915CdE92c2e99dc

▶️ You Can Connect with me on:
Twitter - https://twitter.com/aladdinpersson
LinkedIn - https://www.linkedin.com/in/al....addin-persson-a95384
GitHub - https://github.com/aladdinpersson

TensorFlow Playlist:
https://www.youtube.com/playli....st?list=PLhhyoLH6Ijf

OUTLINE:
0:00 - Introduction
0:48 - Imports
2:21 - Initialization methods for Tensors
8:34 - Casting to different types
9:36 - Mathematical Operations
15:16 - Indexing a Tensor
19:18 - Reshaping a Tensor
20:40 - Ending words

🔥 Edureka Data Science Master Program Training Certification (Use Code: YOUTUBE20) : https://www.edureka.co/masters....-program/data-scient
This Edureka video on 'How to become a Data Scientist' will give you an insight into why the data scientist job is in such a high demand. It then elaborates on different roles and responsibilities of a Data Scientist and what skills are required to fulfill those roles and responsibilities. Then, it build a roadmap that you can follow to become a Data Science Wizard (i.e. Data Scientist) and also it briefly provides you with a sense of how much time it takes to go through the roadmap. The video ends with some incredibly useful resources and courses to help you achieve your goal of becoming a Data Scientist.

00:00:00 Agenda
00:01:28 Why Become a Data Scientist?
00:03:58 What does a Data Scientist do?
00:07:14 Skills Required
00:09:50 How to become a Data Scientist?
00:18:35 Useful Resources

Following pointers are covered in this How to Become an AI Engineer:
1) Why become a Data Scientist?
2) What does a Data Scientist do?
3) Skills required
4) How to become a Data Scientist
5) Useful Resources

------------------------------------

Check out Edureka's Data Science Blog & Tutorial Series to learn more concepts of Data Science:

✅Blog Series: http://bit.ly/data-science-blogs
✅Data Science Tutorial Playlist: http://bit.ly/3tdteya

🔴Subscribe to our channel to get video updates. Hit the subscribe button above: https://goo.gl/6ohpTV

Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
SlideShare: https://www.slideshare.net/EdurekaIN
Castbox: https://castbox.fm/networks/505?country=in
Meetup: https://www.meetup.com/edureka/


#Edureka #DataScience #DataScientistRoadmap #DataScienceCareer #DataScienceCertification #DataScienceTraining #DataScienceMasterProgram #WhatIsDataScience #DataScienceIn2021 #DataScienceCourse #DataScienceEdureka #EdurekaTraining

------------Edureka Online Training and Certification-----------

🔵Data Science Online Training: https://bit.ly/2NCT239
🔵AWS Online Training: https://bit.ly/2ZnbW3s
🔵DevOps Online Training: https://bit.ly/2BPwXf0
🟣Python Online Training: https://bit.ly/2CQYGN7
🟣RPA Online Training: https://bit.ly/2Zd0ac0
🟣Big Data Online Training: https://bit.ly/3g8zksu
🔵Java Online Training: https://bit.ly/31rxJcY
🟣Selenium Online Training: https://bit.ly/3dIrh43
🔵PMP Online Training: https://bit.ly/3dJxMTW
🟣Tableau Online Training: https://bit.ly/3g784KJ

-----------Edureka Masters Programs--------------

🔵Data Scientist Masters Program: https://bit.ly/2YHaolS
🔵Machine Learning Engineer Masters Program: https://bit.ly/388NXJi
🟣Cloud Architect Masters Program: https://bit.ly/3i9z0eJ
🔵DevOps Engineer Masters Program: https://bit.ly/2B9tZCp
🟣Big Data Architect Masters Program: https://bit.ly/31qrOVv
🟣Business Intelligence Masters Program: https://bit.ly/2BPLtn2
🔵Python Developer Masters Program: https://bit.ly/2Vn7tgb
🟣RPA Developer Masters Program: https://bit.ly/3eHwPNf

-------------------------------------------------------

About the Master's Program

This program follows a set structure with 6 core courses and 8 electives spread across 26 weeks. It makes you an expert in key technologies related to Data Science. At the end of each core course, you will be working on a real-time project to gain hands-on expertise. By the end of the program, you will be ready for seasoned Data Science job roles.

----------------------------------------------------

Why should I enroll for the Masters Program?

The Data Scientist Masters Program has been curated after thorough research and recommendations from industry experts. It will help you master concepts of Data Management, Statistics, Machine Learning and Big Data together with hands-on experience of tools & systems used by Data Scientists including Data Visualisation using Tableau. Edureka will be by your side throughout the learning journey - We’re Ridiculously Committed.

----------------------------------------------------

What are the prerequisites for enrollment?

There are no prerequisites for enrollment to the Masters Program. Whether you are an experienced professional working in the IT industry, or an aspirant planning to enter the world of Data Scientist, Masters Program is designed and developed to accommodate various professional backgrounds.

----------------------------------------------------

How long will it take me to be a Certified Data Science professional?

The recommended duration to complete this program is 34 weeks, however, it is up to the individual to complete this program as per their own pace

For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free)

Reviewing Lambda and Razer's Tensorbook, a laptop aimed at deep learning, with 16GB of VRAM (GPU memory), 64GB of RAM, 2TB of NVMe storage and an 8-core intel i7 11800H CPU.
https://lambdalabs.com/deep-le....arning/laptops/tenso

Neural Networks from Scratch book: https://nnfs.io
Channel membership: https://www.youtube.com/channe....l/UCfzlCWGWYyIQ0aLC5
Discord: https://discord.gg/sentdex
Reddit: https://www.reddit.com/r/sentdex/
Support the content: https://pythonprogramming.net/support-donate/
Twitter: https://twitter.com/sentdex
Instagram: https://instagram.com/sentdex
Facebook: https://www.facebook.com/pythonprogramming.net/
Twitch: https://www.twitch.tv/sentdex

DATA is available on the Trimble Learn platform: https://learn.trimble.com/lear....n/course/external/vi

This course is intended to introduce the Deep Learning (Convolutional Neural Network (CNN)) functionalities within the Trimble eCognition Developer Software and consists of 4 videos.

+ Introduction to Deep Learning 1 of 4: Introduction and Set-up
+ Introduction to Deep Learning 2 of 4: Creating Samples
+ Introduction to Deep Learning 3 of 4: Create / Train / Save CNN
+ Introduction to Deep Learning 4 of 4: Apply CNN with OBIA

This course is for free and can be conducted also with the Developer Trial version: https://geospatial.trimble.com/ecognition-trial.

Accessing this course from the Trimble Learn platform, you will have to create an account (also for free) and enroll to this course. Additionally to the DATA you will also receive a CERTIFICATE if you finish the course on the Trimble Learn platform.

Enjoy diving into eCognitions Deep Learning world!

______________Video Content_________________

00:00​ - Introduction
00:29​ - Create a model - Theory
01:46 - Train a model - Theory
02:59 - Create Convolutional Neural Network (alg.)
04:33 - Shuffle labeled sample patches (alg.)
05:27 - Train Convolutional Neural Network (alg.)
06:52 - Save Convolutional Neural Network (alg.)


(⊙_☉)

This Edureka video on 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐂𝐫𝐚𝐬𝐡 𝐂𝐨𝐮𝐫𝐬𝐞 will explain what ChatGPT is all about. In this ChatGPT tutorial, you will learn about how ChatGPT works and the language model that ChatGPT uses.

ChatGPT is an artificial intelligence chatbot developed by OpenAI and launched in November 2022. It is built on top of OpenAI's GPT-3 family of large language models and has been fine-tuned using both supervised and reinforcement learning techniques.

🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐂𝐨𝐮𝐫𝐬𝐞 - 𝐁𝐞𝐠𝐢𝐧𝐧𝐞𝐫𝐬 𝐭𝐨 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝: https://www.edureka.co/openai-....chatgpt-training-cou

⏩ Edureka ChatGPT Explained Playlist: http://bit.ly/3HGRy3G

#ChatGPTCrashCourse #edureka #chatgptexplained #chatgpt #openai #chatgpttutorial #chatgpt3 #ai #nlp #artificialintelligence

Subscribe to our channel to get video updates. Hit the subscribe button above: https://goo.gl/6ohpTV

🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

🔵 DevOps Online Training: http://bit.ly/3VkBRUT
🌕 AWS Online Training: http://bit.ly/3ADYwDY
🔵 React Online Training: http://bit.ly/3Vc4yDw
🌕 Tableau Online Training: http://bit.ly/3guTe6J
🔵 Power BI Online Training: http://bit.ly/3VntjMY
🌕 Selenium Online Training: http://bit.ly/3EVDtis
🔵 PMP Online Training: http://bit.ly/3XugO44
🌕 Salesforce Online Training: http://bit.ly/3OsAXDH
🔵 Data Science Online Training: http://bit.ly/3V3nLrc
🌕 CEHv12 Online Training: http://bit.ly/3Vhq8Hj

🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐑𝐨𝐥𝐞-𝐁𝐚𝐬𝐞𝐝 𝐂𝐨𝐮𝐫𝐬𝐞𝐬

🔵 DevOps Engineer Masters Program: http://bit.ly/3Oud9PC
🌕 Cloud Architect Masters Program: http://bit.ly/3OvueZy
🔵 Data Scientist Masters Program: http://bit.ly/3tUAOiT
🌕 Big Data Architect Masters Program: http://bit.ly/3tTWT0V
🔵 Business Intelligence Masters Program: http://bit.ly/3UZPqJz

🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐔𝐧𝐢𝐯𝐞𝐫𝐬𝐢𝐭𝐲 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐬

🔵 Artificial and Machine Learning PGD with E&ICT Academy
NIT Warangal: http://bit.ly/3OuZ3xs

🌕 Professional Certificate Program in DevOps with Purdue University: https://bit.ly/3Ov52lT

🔵 Advanced Certificate Program in Data Science with E&ICT Academy, IIT Guwahati: http://bit.ly/3V7ffrh

📢📢 𝐓𝐨𝐩 𝟏𝟎 𝐓𝐫𝐞𝐧𝐝𝐢𝐧𝐠 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 𝐭𝐨 𝐋𝐞𝐚𝐫𝐧 𝐢𝐧 2023 𝐒𝐞𝐫𝐢𝐞𝐬 📢📢
⏩ NEW Top 10 Technologies To Learn In 2023 - https://youtu.be/udD_GQVDt5g

🔵 About Edureka ChatGPT Certification Training Course

Edureka’s ChatGPT Certification Training Course will teach you about ChatGPT architecture, GPT models, methodology, and real-world applications. The ChatGPT certification training program is an excellent choice for individuals and organizations seeking to improve their language processing and AI skills and knowledge.

🔵 Why take up the Online ChatGPT Certification Course?

Interested individuals can opt for the Online ChatGPT Certification course as this course provides:

Comprehensive knowledge: The course provides a comprehensive understanding of ChatGPT, including its architecture, training methodology, and real-world applications.

Career advancement: The certification demonstrates an individual's expertise and competence in working with ChatGPT, making them a valuable asset to any organization.

Stay ahead of the curve: ChatGPT is a rapidly growing field, and with the certification, one can stay ahead of the curve and stay updated with the latest advancements in the industry.

Enhance skills: The course provides practical skills and knowledge that can be applied to various areas and industries.

🔵 Who should take up this ChatGPT Certification Course?

The ChatGPT Certification Course is suitable for a wide range of individuals, including:

AI professionals: This course is ideal for AI professionals who want to gain expertise in ChatGPT and expand their knowledge in the field of AI.

Developers: Developers who want to integrate ChatGPT into their projects and create new AI applications can benefit from the course.

Data scientists: Data scientists who want to understand how ChatGPT can be used to process and analyze large amounts of data can also benefit from the course.

📌𝐓𝐞𝐥𝐞𝐠𝐫𝐚𝐦: https://t.me/edurekaupdates
📌𝐋𝐢𝐧𝐤𝐞𝐝𝐈𝐧: https://www.linkedin.com/company/edureka
📌𝐈𝐧𝐬𝐭𝐚𝐠𝐫𝐚𝐦: https://www.instagram.com/edureka_learning/
📌𝐅𝐚𝐜𝐞𝐛𝐨𝐨𝐤: https://www.facebook.com/edurekaIN/
📌𝐒𝐥𝐢𝐝𝐞𝐒𝐡𝐚𝐫𝐞: https://www.slideshare.net/EdurekaIN
📌𝐌𝐞𝐞𝐭𝐮𝐩: https://www.meetup.com/edureka
📌𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐭𝐲: https://www.edureka.co/community/

Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free) for more information.

This course will teach you how to build AI-powered apps with the ChatGPT, Dall-E and GPT-4 APIs. Go here to try the interactive browser-version: https://scrimba.com/learn/buildaiapps

✏️ This course was created by Tom Chant, a teacher at Scrimba. If you have any feedback to Tom, please reach out to him on Twitter here:
https://twitter.com/tpchant

Also, follow Scrimba on YouTube here: https://www.youtube.com/c/Scrimba

We recommend that you learn basic HTML, CSS, and JavaScript before taking this course. Here are two free courses that will get you up to speed:
🔗 HTML & CSS: https://scrimba.com/learn/htmlandcss
🔗 JavaScript: https://scrimba.com/learn/learnjavascript

⭐️ Code ⭐️
🔗 Download via Scrimba: https://scrimba.com/learn/buildaiapps

💫 Links mentioned in course:
🔗 GPT-4 waiting list: https://scrimba.com/links/gpt4-waitlist-openai
🔗 OpenAI Home: https://scrimba.com/links/openai
🔗 OpenAI Docs: https://scrimba.com/links/openai-docs-intro
🔗 OpenAI Completions endpoint docs: https://scrimba.com/links/openai-completions-docs
🔗 GPTTools.com model comparison: https://scrimba.com/links/open-ai-comparison-tool
🔗 OpenAI Playground: https://scrimba.com/links/open-ai-playground
🔗 Dall-E: https://scrimba.com/links/dall-e-openai
🔗 OpenAI endpoint compatibility table: https://scrimba.com/links/chat....gpt-endpoint-compati
🔗 GPT-4 Chatbot conversation object format: https://scrimba.com/links/chatgpt-object-format
🔗 Data used to fine-tune We-Wingit Chatbot: https://scrimba.com/links/we-wingit-data-csv
🔗 Firebase home: https://scrimba.com/links/firebase-home
🔗 Firebase .val() method: https://scrimba.com/links/firebase-val-method
🔗 Object.values MDN: https://scrimba.com/links/object-dot-values
🔗 Netlify: https://scrimba.com/links/netlify-home

⭐️ Contents ⭐️
0:00:00 Introduction
0:01:19 Course Intro
0:04:56 MoviePitch intro
0:07:53 The Boilerplate
0:11:26 Getting an OpenAI API Key
0:13:32 Getting info for fetch request
0:15:14 Building an OpenAI fetch request
0:20:23 The first AI fetch request
0:26:41 Models
0:30:18 Tools
0:34:03 Refactor to use dependency l - env variable
0:38:11 Refactor to use dependency ll - The dependency
0:41:07 Refactor to use dependency lll - update fetchReply
0:44:40 Take out of Scrimba
0:46:45 Personalising the message
0:53:04 Tokens
0:57:09 fetchSynopsis
1:03:44 Aside - few shot approach
1:10:45 Aside - few shot approach ll
1:13:42 Refactor fetchSynopsis
1:21:00 Architecture
1:23:23 Title and Temperature
1:31:52 Reaching for the stars
1:37:52 Aside - createImage
1:46:56 fetchImagePrompt
1:54:21 Displaying the image and finishing off the UX
2:03:16 OutroKnowItAll: GPT-4 Chatbox2:06:47 KnowItAll Intro
2:09:40 Starter Code
2:13:10 Aside: How ChatGPT models work for chatbots
2:18:24 Conversation and instructions
2:20:21 Add user input to conversation array
2:23:06 The createChatCompletion endpoint
2:24:38 The model and object
2:28:46 Render the output, update the array
2:33:37 Aside: Theory: Frequency and presence penalties
2:37:07 presence_penalty practice
2:38:36 frequency_penalty practice
2:44:54 The chatbot’s personality
2:47:06 Firebase Intro
2:48:27 Firebase Account and database set up
2:50:43 Firebase dependency and database set up
2:55:53 Push method and instructions object
2:58:33 Update fetch Reply
3:02:24 Update fetchReply 2
3:04:49 Update the database
3:07:19 Render the conversation from the DB
3:12:02 The “start over” button
3:15:20 OutroWe-Wingit: Fine-tuned chatbot3:17:28 Intro to fine-tuning
3:20:04 Convert the Chatbot to We-Wingit
3:22:15 An Overview of the AI
3:23:52 Data for fine-tuning
3:26:34 The data we’re using
3:30:05 CLI 1 - Setting up the environment
3:33:03 CLI 2 - Data Preparation Tool
3:37:03 CLI 3 - Tuning the model
3:38:55 Updating the JS 1
3:41:33 Updating the JS 2
3:44:15 Updating the JS 3
3:47:01 The Separator
3:52:32 Aside - Stop Sequence
3:55:50 Adding the stop sequence
4:00:36 n_epochs
4:07:24 Intro to deployment
4:09:46 Download and GitHub
4:12:07 Netlify sign-up
4:13:56 Add Netlify env var
4:15:54 Netlify CLI
4:17:30 Netlify serverless function 1
4:19:52 Update fetchReply
4:24:28 Serverless function 2
4:27:30 Serverless function 3
4:29:21 Serverless function 4
4:32:32 Outro

🎉 Thanks to our Champion and Sponsor supporters:
👾 davthecoder
👾 jedi-or-sith
👾 南宮千影
👾 Agustín Kussrow
👾 Nattira Maneerat
👾 Heather Wcislo
👾 Serhiy Kalinets
👾 Justin Hual
👾 Otis Morgan

--

Learn to code for free and get a developer job: https://www.freecodecamp.org

Read hundreds of articles on programming: https://freecodecamp.org/news

In this video I'll be teaching you how to make your own command line chat gpt that you can use while you can't get access to openai's chat gpt front end. I'll show you in less than 5 minutes how to get it running on free hardware. If you enjoy learning about AI subscribe because this will be one of many open source AI projects I'll be showing you how to run.

🔗 Links
Google Colab | Free Version of Chat GPT - http://bit.ly/3kIpwNo
Github CODE | Run Locally - http://bit.ly/3Df8rRw
Open AI Website - https://openai.com/

📺 Other AI Videos
Clone Voices - http://bit.ly/3XAOU68
Make Art - https://bit.ly/3WSVC6B

🌎 Socials
Twitter - https://twitter.com/TheCodingBranch
GitHub - https://github.com/TheCodingBranch

#googlecolab #googlecloud #openai #chatgpt #commandline #freeai

*Note: 1+ Years of Work Experience Recommended to Sign up for Below Programs⬇️
🔥Post Graduate Program In Data Engineering: https://www.simplilearn.com/pgp-data-engineering-certification-training-course?utm_campaign=BigData-aReuLtY0YMI-aReuLtY0YMI&utm_medium=Descriptionff&utm_source=youtube
🔥Big Data Engineer Masters Program (Discount Code - YTBE15): https://www.simplilearn.com/big-data-engineer-masters-program?utm_campaign=BigData-aReuLtY0YMI-aReuLtY0YMI&utm_medium=Descriptionff&utm_source=youtube
Hadoop is a famous Big Data framework; this video on Hadoop will acquaint you with the term Big Data and help you understand the importance of Hadoop. Here, you will also learn about the three main components of Hadoop, namely, HDFS, MapReduce, and YARN. In the end, we will have a quiz on Hadoop. Hadoop is a framework that manages Big Data storage in a distributed way and processes it parallelly. Now, let's get started and learn all about Hadoop.

Don't forget to take the quiz at 05:11!

To learn more about Hadoop, subscribe to our YouTube channel: https://www.youtube.com/user/S....implilearn?sub_confi

Watch more videos on HadoopTraining: https://www.youtube.com/watch?v=CKLzDWMsQGM&list=PLEiEAq2VkUUJqp1k-g5W1mo37urJQOdCZ

#WhatIsHadoop #Hadoop #HadoopExplained #IntroductionToHadoop #HadoopTutorial #Simplilearn Big Data #SimplilearnHadoop #simplilearn

➡️ Post Graduate Program In Data Engineering
This Data Engineering course is ideal for professionals, covering critical topics like the Hadoop framework, Data Processing using Spark, Data Pipelines with Kafka, Big Data on AWS, and Azure cloud infrastructures. This program is delivered via live sessions, industry projects, masterclasses, IBM hackathons, and Ask Me Anything sessions.

✅ Key Features
- Professional Certificate Program Certificate and Alumni Association membership
- Exclusive Master Classes and Ask me Anything sessions by IBM
- 8X higher live interaction in live Data Engineering online classes by industry experts
- Capstone from 3 domains and 14+ Projects with Industry datasets from YouTube, Glassdoor, Facebook etc.
- Master Classes delivered by Purdue faculty and IBM experts
- Simplilearn's JobAssist helps you get noticed by top hiring companies

✅ Skills Covered
- Real Time Data Processing
- Data Pipelining
- Big Data Analytics
- Data Visualization
- Provisioning data storage services
- Apache Hadoop
- Ingesting Streaming and Batch Data
- Transforming Data
- Implementing Security Requirements
- Data Protection
- Encryption Techniques
- Data Governance and Compliance Controls

👉Learn More at: https://www.simplilearn.com/pgp-data-engineering-certification-training-course?utm_campaign=BigData-aReuLtY0YMI&utm_medium=Description&utm_source=youtube

🔥🔥 Interested in Attending Live Classes? Call Us: IN - 18002127688 / US - +18445327688

🎓Enhance your expertise in the below technologies to secure lucrative, high-paying job opportunities:
🟡 AI & Machine Learning - https://l.linklyhq.com/l/1tMt8
🟢 Cyber Security - https://l.linklyhq.com/l/1tMt9
🔴 Data Analytics - https://l.linklyhq.com/l/1tMt1
🟠 Data Science - https://l.linklyhq.com/l/1tMt4
🔵 Cloud Computing - https://l.linklyhq.com/l/1tMtA

IQ is supposed to measure intelligence, but does it? Head to https://brilliant.org/veritasium to start your free 30-day trial, and the first 200 people get 20% off an annual premium subscription.

If you’re looking for a molecular modeling kit, try Snatoms – a kit I invented where the atoms snap together magnetically – https://ve42.co/SnatomsV

▀▀▀
A huge thank you to Emeritus Professor Cecil R. Reynolds and Dr. Stuart J. Ritchie for their expertise and time.

Also a massive thank you to Prof. Steven Piantadosi and Prof. Alan S. Kaufman for helping us understand this complicated topic. As well as to Jay Zagrosky from Boston University's Questrom School of Business for providing data from his study.

▀▀▀
References:
Kaufman, A. S. (2009). IQ testing 101. Springer Publishing Company.

Reynolds, C. R., & Livingston, R. A. (2021). Mastering modern psychological testing. Springer International Publishing.

Ritchie, S. (2015). Intelligence: All that matters. John Murray.

Spearman, C. (1961). " General Intelligence" Objectively Determined and Measured. - https://ve42.co/Spearman1904

Binet, A., & Simon, T. (1907). Le développement de l'intelligence chez les enfants. L'Année psychologique, 14(1), 1-94.. - https://ve42.co/Binet1907

Intelligence Quotient, Wikipedia - https://ve42.co/IQWiki

Radiolab Presents: G. - https://ve42.co/RadioLabG

McDaniel, M. A. (2005). Big-brained people are smarter: A meta-analysis of the relationship between in vivo brain volume and intelligence. Intelligence, 33(4), 337-346. - https://ve42.co/McDaniel2005

Deary, I. J., Strand, S., Smith, P., & Fernandes, C. (2007). Intelligence and educational achievement. Intelligence, 35(1), 13-21. - https://ve42.co/Deary2007

Lozano-Blasco, R., Quílez-Robres, A., Usán, P., Salavera, C., & Casanovas-López, R. (2022). Types of Intelligence and Academic Performance: A Systematic Review and Meta-Analysis. Journal of Intelligence, 10(4), 123. - https://ve42.co/Blasco2022

Kuncel, N. R., & Hezlett, S. A. (2010). Fact and fiction in cognitive ability testing for admissions and hiring decisions. Current Directions in Psychological Science, 19(6), 339-345. - https://ve42.co/Kuncel2010

Laurence, J. H., & Ramsberger, P. F. (1991). Low-aptitude men in the military: Who profits, who pays?. Praeger Publishers. - https://ve42.co/Laurence1991

Gregory, H. (2015). McNamara's Folly: The Use of Low-IQ Troops in the Vietnam War; Plus the Induction of Unfit Men, Criminals, and Misfits. Infinity Publishing.

Gottfredson, L. S., & Deary, I. J. (2004). Intelligence predicts health and longevity, but why?. Current Directions in Psychological Science, 13(1), 1-4. - https://ve42.co/Gottfredson2004

Sanchez-Izquierdo, M., Fernandez-Ballesteros, R., Valeriano-Lorenzo, E. L., & Botella, J. (2023). Intelligence and life expectancy in late adulthood: A meta-analysis. Intelligence, 98, 101738. - https://ve42.co/Izquierdo2023

Zagorsky, J. L. (2007). Do you have to be smart to be rich? The impact of IQ on wealth, income and financial distress. Intelligence, 35(5), 489-501. - https://ve42.co/Zagorsky2007

Strenze, T. (2007). Intelligence and socioeconomic success: A meta-analytic review of longitudinal research. Intelligence, 35(5), 401-426. - https://ve42.co/Strenze2007

Deary, I. J., Pattie, A., & Starr, J. M. (2013). The stability of intelligence from age 11 to age 90 years: the Lothian birth cohort of 1921. Psychological science, 24(12), 2361-2368. - https://ve42.co/Deary2013

Flynn, J. R. (1987). Massive IQ gains in 14 nations: What IQ tests really measure. Psychological bulletin, 101(2), 171. - https://ve42.co/Flynn1987

Why our IQ levels are higher than our grandparents' | James Flynn, TED via YouTube - https://www.youtube.com/watch?v=9vpqilhW9uI

Duckworth, A. L., Quinn, P. D., Lynam, D. R., Loeber, R., & Stouthamer-Loeber, M. (2011). Role of test motivation in intelligence testing. Proceedings of the National Academy of Sciences, 108(19), 7716-7720. - https://ve42.co/Duckworth2011

Kulik, J. A., Bangert-Drowns, R. L., & Kulik, C. L. C. (1984). Effectiveness of coaching for aptitude tests. Psychological Bulletin, 95(2), 179. - https://ve42.co/Kulik1984

▀▀▀
Special thanks to our Patreon supporters:
Adam Foreman, Amadeo Bee, Anton Ragin, Balkrishna Heroor, Benedikt Heinen, Bernard McGee, Bill Linder, Burt Humburg, Dave Kircher, Diffbot, Evgeny Skvortsov, Gnare, John H. Austin, Jr., john kiehl, Josh Hibschman, Juan Benet, KeyWestr, Lee Redden, Marinus Kuivenhoven, MaxPal, Meekay, meg noah, Michael Krugman, Orlando Bassotto, Paul Peijzel, Richard Sundvall, Sam Lutfi, Stephen Wilcox, Tj Steyn, TTST, Ubiquity Ventures

▀▀▀
Written by Derek Muller, Casper Mebius, & Petr Lebedev
Edited by Trenton Oliver
Filmed by Derek Muller, Han Evans, & Raquel Nuno
Animation by Fabio Albertelli & Ivy Tello
Additional video/photos supplied by Getty Images & Pond5
Music from Epidemic Sound
Produced by Derek Muller, Casper Mebius, & Han Evans

The truth, with photons.
I hope I've articulated everything clearly in this video. If not, I'll clarify in comments. Thanks to everyone who appears in this video and thanks to everyone who watches this video!

Veritasium is of course a combination of the latin 'veritas' meaning truth, and the common element ending 'ium'. I guess this is my version of the 'draw my life' craze that rolled through YouTube many years ago. Except I wanted to tell my story with the actual moments, the photons, the stored magnetic states. There's something about that which is so important to me (because I think the alternative involves fooling yourself) which is why I'm so fascinated by film and video.

One of my inspirations for the name Veritasium came from the end of the poem Ode on a Grecian Urn by John Keats, in which he writes:
"Beauty is truth, truth beauty,—that is all
Ye know on earth, and all ye need to know."

Special thanks to Patreon supporters:
Tony Fadell, Donal Botkin, Michael Krugman, Jeff Straathof, Zach Mueller, Ron Neal, Nathan Hansen, Yildiz Kabaran,
Terrance Snow, Stan Presolski

Music from http://epidemicsound.com
Magnified X1 - Gunnar Johnsen
Fluorescent Lights - Martin Gauffin
Dissolving Patterns - Ebb & Flod
Luna - Ebb & Flod

Additional music by Kevin MacLeod: http://incompetech.com
Sneaky Snitch

🔥Edureka Python Certification Training: https://www.edureka.co/machine....-learning-certificat
This Edureka video on 'Support Vector Machine Tutorial' covers A brief introduction to Support Vector Machine in Python with a use case to implement SVM using Python.

🔷🔸About the Speaker🔸🔷
Name: Dr. Rajesh Kumar
Details:
◾Data Science Head at SCG Chemicals
◾Ex - Ernst & Young, Ex-Intel, Ex - Mercedes Benz
◾16 years of experience spanning across IT Services, Petrochemicals, Hi-Tech, Business Consulting, Supply Chain, and Automotive Industries.
◾A Ph.D. holder from the Indian Institute of Science
----------------------------------------------------------------------------------
Python Tutorial Playlist: https://goo.gl/WsBpKe
Blog Series: http://bit.ly/2sqmP4s

🔴Subscribe to our channel to get video updates. Hit the subscribe button above: https://goo.gl/6ohpTV

Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
SlideShare: https://www.slideshare.net/EdurekaIN
Castbox: https://castbox.fm/networks/505?country=in
Meetup: https://www.meetup.com/edureka

#Edureka #PyhtonEdureka #Supportvectormachineinpython #pythonprojects #pythonprogramming #pythontutorial #PythonTraining #PythonEdureka learn #withme


-----------------------------------------------------------------------------------------------------------------------------------


How it Works?
1. This is a 5 Week Instructor-led Online Course,40 hours of assignment and 20 hours of project work
2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. At the end of the training, you will be working on a real-time project for which we will provide you a Grade and a Verifiable Certificate!

- - - - - - - - - - - - - - - - -
About the Course

Edureka's Python Online Certification Training will make you an expert in Python programming. It will also help you learn Python the Big data way with integration of Machine learning, Pig, Hive and Web Scraping through beautiful soup. During our Python Certification training, our instructors will help you:

1. Master the Basic and Advanced Concepts of Python
2. Understand Python Scripts on UNIX/Windows, Python Editors and IDEs
3. Master the Concepts of Sequences and File operations
4. Learn how to use and create functions, sorting different elements, Lambda function, error handling techniques and Regular expressions ans using modules in Python
5. Gain expertise in machine learning using Python and build a Real Life Machine Learning application
6. Understand the supervised and unsupervised learning and concepts of Scikit-Learn
7. Master the concepts of MapReduce in Hadoop
8. Learn to write Complex MapReduce programs
9. Understand what is PIG and HIVE, Streaming feature in Hadoop, MapReduce job running with Python
10. Implementing a PIG UDF in Python, Writing a HIVE UDF in Python, Pydoop and/Or MRjob Basics
11. Master the concepts of Web scraping in Python
12. Work on a Real Life Project on Big Data Analytics using Python and gain Hands on Project Experience
- - - - - - - - - - - - - - - - - - -

Why learn Python?

Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations.
Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license.
Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain.

Who should go for python?

Edureka’s Data Science certification course in Python is a good fit for the below professionals:


· Programmers, Developers, Technical Leads, Architects
· Developers aspiring to be a ‘Machine Learning Engineer'
· Analytics Managers who are leading a team of analysts
· Business Analysts who want to understand Machine Learning (ML) Techniques
· Information Architects who want to gain expertise in Predictive Analytics
· 'Python' professionals who want to design automatic predictive models


For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free)

Demystifying attention, the key mechanism inside transformers and LLMs.
Instead of sponsored ad reads, these lessons are funded directly by viewers: https://3b1b.co/support
Special thanks to these supporters: https://www.3blue1brown.com/le....ssons/attention#than
An equally valuable form of support is to simply share the videos.

Demystifying self-attention, multiple heads, and cross-attention.
Instead of sponsored ad reads, these lessons are funded directly by viewers: https://3b1b.co/support

The first pass for the translated subtitles here is machine-generated, and therefore notably imperfect. To contribute edits or fixes, visit https://translate.3blue1brown.com/

And yes, at 22:00 (and elsewhere), "breaks" is a typo.

------------------

Here are a few other relevant resources

Build a GPT from scratch, by Andrej Karpathy
https://youtu.be/kCc8FmEb1nY

If you want a conceptual understanding of language models from the ground up, @vcubingx just started a short series of videos on the topic:
https://youtu.be/1il-s4mgNdI?si=XaVxj6bsdy3VkgEX

If you're interested in the herculean task of interpreting what these large networks might actually be doing, the Transformer Circuits posts by Anthropic are great. In particular, it was only after reading one of these that I started thinking of the combination of the value and output matrices as being a combined low-rank map from the embedding space to itself, which, at least in my mind, made things much clearer than other sources.
https://transformer-circuits.p....ub/2021/framework/in

Site with exercises related to ML programming and GPTs
https://www.gptandchill.ai/codingproblems

History of language models by Brit Cruise,  @ArtOfTheProblem 
https://youtu.be/OFS90-FX6pg

An early paper on how directions in embedding spaces have meaning:
https://arxiv.org/pdf/1301.3781.pdf

------------------

Timestamps:
0:00 - Recap on embeddings
1:39 - Motivating examples
4:29 - The attention pattern
11:08 - Masking
12:42 - Context size
13:10 - Values
15:44 - Counting parameters
18:21 - Cross-attention
19:19 - Multiple heads
22:16 - The output matrix
23:19 - Going deeper
24:54 - Ending

------------------

These animations are largely made using a custom Python library, manim. See the FAQ comments here:
https://3b1b.co/faq#manim
https://github.com/3b1b/manim
https://github.com/ManimCommunity/manim/

All code for specific videos is visible here:
https://github.com/3b1b/videos/

The music is by Vincent Rubinetti.
https://www.vincentrubinetti.com
https://vincerubinetti.bandcam....p.com/album/the-musi
https://open.spotify.com/album..../1dVyjwS8FBqXhRunaG5

------------------

3blue1brown is a channel about animating math, in all senses of the word animate. If you're reading the bottom of a video description, I'm guessing you're more interested than the average viewer in lessons here. It would mean a lot to me if you chose to stay up to date on new ones, either by subscribing here on YouTube or otherwise following on whichever platform below you check most regularly.

Mailing list: https://3blue1brown.substack.com
Twitter: https://twitter.com/3blue1brown
Instagram: https://www.instagram.com/3blue1brown
Reddit: https://www.reddit.com/r/3blue1brown
Facebook: https://www.facebook.com/3blue1brown
Patreon: https://patreon.com/3blue1brown
Website: https://www.3blue1brown.com

Best Courses for Analytics:
---------------------------------------------------------------------------------------------------------
+ IBM Data Science (Python): https://bit.ly/3Rn00ZA
+ Google Analytics (R): https://bit.ly/3cPikLQ
+ SQL Basics: https://bit.ly/3Bd9nFu


Best Courses for Programming:
---------------------------------------------------------------------------------------------------------
+ Data Science in R: https://bit.ly/3RhvfFp
+ Python for Everybody: https://bit.ly/3ARQ1Ei
+ Data Structures & Algorithms: https://bit.ly/3CYR6wR


Best Courses for Machine Learning:
---------------------------------------------------------------------------------------------------------
+ Math Prerequisites: https://bit.ly/3ASUtTi
+ Machine Learning: https://bit.ly/3d1QATT
+ Deep Learning: https://bit.ly/3KPfint
+ ML Ops: https://bit.ly/3AWRrxE


Best Courses for Statistics:
---------------------------------------------------------------------------------------------------------
+ Introduction to Statistics: https://bit.ly/3QkEgvM
+ Statistics with Python: https://bit.ly/3BfwejF
+ Statistics with R: https://bit.ly/3QkicBJ


Best Courses for Big Data:
---------------------------------------------------------------------------------------------------------
+ Google Cloud Data Engineering: https://bit.ly/3RjHJw6
+ AWS Data Science: https://bit.ly/3TKnoBS
+ Big Data Specialization: https://bit.ly/3ANqSut


More Courses:
---------------------------------------------------------------------------------------------------------
+ Tableau: https://bit.ly/3q966AN
+ Excel: https://bit.ly/3RBxind

+ Computer Vision: https://bit.ly/3esxVS5
+ Natural Language Processing: https://bit.ly/3edXAgW

+ IBM Dev Ops: https://bit.ly/3RlVKt2
+ IBM Full Stack Cloud: https://bit.ly/3x0pOm6
+ Object Oriented Programming (Java): https://bit.ly/3Bfjn0K

+ TensorFlow Advanced Techniques: https://bit.ly/3BePQV2
+ TensorFlow Data and Deployment: https://bit.ly/3BbC5Xb
+ Generative Adversarial Networks / GANs (PyTorch): https://bit.ly/3RHQiRj


Become a Member of the Channel! https://bit.ly/3oOMrVH
Follow me on LinkedIn! https://www.linkedin.com/in/greghogg/


Full Disclosure:
Please note that I may earn a commission for purchases made at the above sites! I strongly believe in the material provided; I only recommend what I truly think is great. If you do choose to make purchases through these links; thank you for supporting the channel, it helps me make more free content like this!

🔥Data Analyst Masters Program (Discount Code - YTBE15) - https://www.simplilearn.com/data-analyst-masters-certification-training-course?utm_campaign=DoANDQMAmIg&utm_medium=DescriptionFirstFold&utm_source=Youtube
🔥IITK - Professional Certificate Course in Data Analytics and Generative AI (India Only) - https://www.simplilearn.com/iitk-professional-certificate-course-data-analytics?utm_campaign=DoANDQMAmIg&utm_medium=DescriptionFirstFold&utm_source=Youtube
🔥Purdue - Post Graduate Program in Data Analytics - https://www.simplilearn.com/pgp-data-analytics-certification-training-course?utm_campaign=DoANDQMAmIg&utm_medium=DescriptionFirstFold&utm_source=Youtube
🔥Caltech - Data Analytics Bootcamp (US Only) - https://www.simplilearn.com/data-analytics-bootcamp?utm_campaign=DoANDQMAmIg&utm_medium=DescriptionFirstFold&utm_source=Youtube
🔥IITG - Professional Certificate Program in Data Analytics and Generative AI (India Only) - https://www.simplilearn.com/iitg-generative-ai-data-analytics-program?utm_campaign=DoANDQMAmIg&utm_medium=DescriptionFirstFold&utm_source=Youtube

This Excel Full course video by simplilearn will help you learn Microsoft excel from basics to advanced concepts. This Introduction to Excel Full Course provides a detailed guide to learning Excel and related data analytics tools. Starting with what Microsoft Excel is, the course offers an Excel tutorial for beginners, teaching you the basics. You'll learn advanced features like Microsoft Power Query and how to use Copilot in Excel for enhanced productivity. The course covers 10 essential Excel formulas, explains the concept of DBMS, and explores data analytics using AI. It also compares Data Science vs. Data Analytics and outlines a roadmap to becoming a data analyst. Additionally, it introduces key BI terms every data analyst should know and demonstrates how to use ChatGPT to build an Excel dashboard. To solidify your skills, it concludes with the top 10 data analyst projects for your portfolio, providing practical insights to excel in your career.

00:00:00 Introduction to Excel Full Course
00:03:55 What is Microsoft Excel
05:42:00 Excel Tutorial For Beginners
06:03:24 How to use Microsoft power query
06:12:45 Copilot In EXCEL
06:36:31 10 important excel formulas
06:37:39 What is DBMS
06:48:32 Data Analytics using AI
07:12:59 Data Science Vs Data Analyst
07:31:40 Data Analyst Roadmap
07:32:29 Top BI Terms every data analyst know
08:09:23 How to use ChatGPT to built an Excel Dashboard
08:21:58 Top 10 Data Analyst Projects for your portfolio

⏩ Check out the Excel tutorial videos: https://www.youtube.com/watch?v=nPkmWE4JCfE&list=PLEiEAq2VkUUKf8aLrspLg3zuyJ5S-5K5S

#excelfullcourse #excelcourse #excel #exceldataanalytics #exceltraining #excelformulasandfunctions #exceldatavisualization #simplilearn #2024

➡️ About Post Graduate Program In Data Analytics
This Data Analytics Program is ideal for all working professionals and prior programming knowledge is not required. It covers topics like data analysis, data visualization, regression techniques, and supervised learning in-depth via our applied learning model with live sessions by leading practitioners and industry projects.

Key Features
✅ Post Graduate Program certificate and Alumni Association membership
✅ Exclusive hackathons and Ask me Anything sessions by IBM
✅ 8X higher live interaction in live online classes by industry experts
✅ Capstone from 3 domains and 14+ Data Analytics Projects with Industry datasets from Google PlayStore, Lyft, World Bank etc.
✅ Master Classes delivered by Purdue faculty and IBM experts
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies
✅ Resume preparation and LinkedIn profile building
✅ 1:1 mock interview
✅ Career accelerator webinars

Skills Covered
✅ Data Analytics
✅ Statistical Analysis using Excel
✅ Data Analysis Python and R
✅ Data Visualization Tableau and Power BI
✅ Linear and logistic regression modules
✅ Clustering using kmeans
✅ Supervised Learning

👉 Learn More at: https://www.simplilearn.com/pgp-data-analytics-certification-training-course?utm_campaign=DoANDQMAmIg&utm_medium=Description&utm_source=youtube

Ready to become a certified watsonx AI Assistant Engineer? Register now and use code IBMTechYT20 for 20% off of your exam → https://ibm.biz/Bdnd3d

Learn more about Large Language Models (LLMs) here → https://ibm.biz/Bdnd3x

What if you could run large language models locally with just one command? 🚀 Cedric Clyburn shows how Ollama, an open-source tool, simplifies deploying LLMs on your machine. 💡 Protect your data, save costs, and explore powerful AI solutions—all from your own system. ✨

AI news moves fast. Sign up for a monthly newsletter for AI updates from IBM → https://ibm.biz/Bdnd3D

#ollama #opensourceai #llm

MIT 6.7960 Deep Learning, Fall 2024
Instructor: Sara Beery
View the complete course: https://ocw.mit.edu/courses/6-....7960-deep-learning-f
YouTube Playlist: https://www.youtube.com/playli....st?list=PLUl4u3cNGP6

This video provides a course overview and introduces deep neural networks, covering their fundamental concepts and basic building blocks. It sets the stage for understanding how these models work and what components they are built from.

License: Creative Commons BY-NC-SA
More information at https://ocw.mit.edu/terms
More courses at https://ocw.mit.edu
Support OCW at http://ow.ly/a1If50zVRlQ

We encourage constructive comments and discussion on OCW’s YouTube and other social media channels. Personal attacks, hate speech, trolling, and inappropriate comments are not allowed and may be removed. More details at https://ocw.mit.edu/comments.